Objective bayesian analysis for the gompertz distribution under doudly type II cesored data

Trimmed samples are widely utilized in several areas of statistical practice, especially when some sample values at either or both extremes might have been adulterated. In this article, the problem of estimating the parameter of Gompertz distribution based on trimmed samples under informative and non-informative priors has been addressed. The problem discussed using Bayesian approach to estimate the parameter of Gompertz distribution. We have examined Bayes estimates under symmetric and asymmetric loss functions. The explicit expressions for estimator and risk are developed under all loss functions. Elicitation of hyperparameter through prior predictive approach is also discussed. Posterior Predictive distributions and Credible Intervals are also derived under different priors. The influence of parametric value on the estimate and risk is also discussed. Finally, to assess the performance of the estimators, numerical results using Monte Carlo simulation study are reported.

Keywords:

Inverse transformation method , Doubly censored samples , Loss functions , Credible intervals , Posterior predictive distributions